Background: Tuberculosis remains an important public health problem especially in sub-Saharan Africa. Nigeria currently ranks 4th among the 22 high Tuberculosis (TB) burden countries with an estimated prevalence of 338/100,000 population. Few studies have utilized spatial data analysis techniques in the understanding of the pattern of distribution and possible correlates of TB especially in Africa. This study examines the spatial distribution of TB and its associated socioeconomic determinants in Nigeria. Methods: The study used an ecological design based on the 774 Local Government Areas (LGAs) in Nigeria as the spatial units. Initial exploratory analysis used measures of spatial autocorrelation (Global and Local Moran’s test statistics). The associations between TB incidence and nine covariates were assessed using a spatial regression analysis in the R statistical package. Result: A total of 100,217 TB cases were notified in 2013. There is significant spatial autocorrelation among case notifications rates (CNR). Spatial regression analysis identifies 138 (17%) of LGAs with high TB risks and finds a significant relationship between household size, urban residence access to transportation, population density, number of TB diagnostic services and TB. An index defining socioeconomic status, living in a single room, TB treatment centres and total health facilities are not significantly associated with TB CNR. Conclusion: The study presents a national picture of TB spatial heterogeneity at the lowest administrative level in Nigeria with the identification of high risk LGAs. This information can assist policy makers to rationally plan targeted specific interventions to effectively control TB while addressing the underlying socioeconomic risk factors in the country.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:705967 |
| Date | January 2017 |
| Creators | Daniel, Olusoji |
| Contributors | Gatrell, Tony ; Zucchelli, Eugenio |
| Publisher | Lancaster University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.lancs.ac.uk/85146/ |
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